Weather map photo satellite illustrations and profile completion.

and radar images. How do we counter deficiencies in this information? Check this basket of tricks we use to integrate these things. To supply missing details.

First of all we use facts from various sources to make vertical outlines of key variables. Technicians use computer programs to chart dew point, temperature and other quantities for us.

You would then need to develop a 3D representation of each quantity. This product serves as input for forecasting models and vertical mapping software. These computer programs handle vast amounts of data.

See satellite photos from:

Advanced uses for satellite data

Fitting into the big picture

An essential meteorological device,
the radiosonde,
follows a weather balloon up through the atmosphere from a launch station. The radiosonde takes measurements of
temperature,
humidity,
wind
etc. It then transmits the information back to the station by radio waves.

After we place the data on the map photo satellite
images
and drawings are ready for analysis. You can then compare the radiosonde data to
satellite images.
This is of great, but still limited value.

One problem is, we send this expensive little equipment package from each dispatch station only twice each day. If satellites could replace this old technology it would be much more efficient. At least satellite information can
enhance
vertical profiles derived by other means. Especially over oceans and other remote regions.

This type of map photo satellite usage is more sophisticated, and techniques will continue to progress.

How to make the map photo satellite profiles?

Various filters change the nature of the scanned images.

Supplementary data is added and then we run it through more computers to customize it.

The scanner on each
weather satellite
uses many wavelengths to dance around the absorption spectrums of atmospheric gases. These bands vary for carbon dioxide, oxygen, water vapour and ozone.

Complicated mathematics can sort out small differences in intensities by light spectrum wavelengths. We identify substances by comparing our traces with known compositions.

Atmosphere layers
stop radiation from below and re-emit it upwards. This affects what the map photo satellite actually sees. The radiation the satellite receives depends largely on the emitting layers. How do we fill in the information gaps left behind?

At other wavelengths, the layer's weaker absorption permits some of the radiation from the surface and lower atmosphere to penetrate and reach the satellite directly. A lot of research went into devising weighting functions and simpler algorithms distinguish meaning from this chaos.

Physical Science Tests

Oxygen and carbon dioxide are distributed evenly throughout the atmosphere. This scattering makes them useful for creating a satellite temperature sounding. We use the data and other physical properties to determine
humidity
and ozone profiles.

Clouds complicate this even further. Microwaves from the earth give us additional information to help with this problem, even though they are distorted by rain. Precipitation stops microwaves. That is what makes
radar
useful.

All this allows us to build temperature and humidity profiles in cloudy areas. It is best, though, to use these numbers to fortify infra-red data and make a more complete picture. How complete?

We need good vertical resolution, less than a kilometre for sure, for this to be any good. Problems with thin layers and inversion temperature anomalies, increasing temperature with height, lead to ambiguity in the photographs. This means we can derive more than one possible solution from the available data.

Enter…statistical analysis! Researchers construct profiles using trial and error. They construct empirical correlations between measured and expected values to fill in the gaps.

How? Mathematical variables are derived using linear regression statistics and other formulae. The computers use them to work out deviation vectors and make a more realistic profile by adjusting a standardized profile.

Meteorology and Statistics

As with all guesswork, challenges arise in accuracy, especially when good map photo satellite data is sparse. Sometimes the first guess is taken too seriously without being all that good. How do we fix that problem?

Intense explorations and longitudinal studies gradually improve this. As pattern recognition software develops and data libraries continue to grow, solutions will appear for non-linear physics problems and even initial estimates will get better.

Increasingly powerful computers make the huge math more manageable. Iterative calculations, those that must be repeated many times, can now be done in a practical amount of time and allow us to get more helpful information from less data.

Newer map photo satellite equipment will do their jobs even better. Also, continuing investigations into theory will make interpreting the pictures and images more feasible.

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